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Connect Google Ad Manager to PostgreSQL

Connect Google Ad Manager to PostgreSQL and export selected accounts, metrics, and dimensions to your PostgreSQL project.

Configure the historical window, destination table, and recurring schedule without maintaining a Google Ad Manager API pipeline.

Used by the world's leading companies

Export Google Ad Manager data to PostgreSQL

Catchr handles extraction, normalization, and loading automatically.

Centralize

Centralize Google Ad Manager data in PostgreSQL

Bring all your Google Ad Manager data into your warehouse and make it available for analytics, machine learning, and internal applications.

Data freshness

Keep your PostgreSQL tables up to date

Automatically sync new data from Google Ad Manager so every dashboard, model, and report works with fresh information.

Analysis

Unify Google Ad Manager with the rest of your business data

Join marketing, finance, CRM, and product data inside the same warehouse.

Google Ad Manager metrics and dimensions available in PostgreSQL

Access 321 metrics and 488 dimensions from Google Ad Manager connectors including Total revenue, Ad server total revenue, Ad Exchange revenue, Ad server average eCPM, Total clicks, Total CTR, Total Active View % viewable impressions, Date, Country, Inventory type, Device category, Line item, Order, Creative, Domain and many more...

321

Metrics availables

488

Dimensions availables

Connect Google Ad Manager to PostgreSQL in minutes

Move your data from Google Ad Manager to PostgreSQL with a simple setup. Once connected, Catchr handles the ingestion automatically so your warehouse stays up to date without manual work.

Step one

Connect your Google Ad Manager account

Authenticate your Google Ad Manager account securely in Catchr. No custom scripts, API maintenance, or engineering work required.

Client A · Connected sources
5 sources ready
Google Ad Manager 3 advertising accounts Connected
Google Ads 2 advertising accounts Connected
Google Analytics 4 1 web property Connected
HubSpot 1 CRM portal Connected
Step two

Choose the PostgreSQL destination

Add the database host and credentials once. Catchr checks the connection so your exports start with a reachable destination.

Destination / PostgreSQL Required fields
Host Required
warehouse.company.net
Username Required
catchr_writer
Password Required
••••••••••••
Database Required
marketing
Step three

Keep your PostgreSQL tables updated

Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your PostgreSQL table.

Export job / PostgreSQL Example
Schema Destination
marketing_raw
Table Per job
linkedin_ads_daily
Recurring schedule Choose a cadence
Every 6 hours
Daily · 07:00
Weekly · Mon
First sync scheduledSelected fields · configured history
07:00 UTC

Google Ad Manager.sql
BigQuery SQL
30-day window
Illustrative SQL — adapt it to the fields and schema selected in your export. Standard SQL

Choose what to load into PostgreSQL.

Each connector has its own entities, fields, historical limits, and reporting uses. Open a source page for the details that belong to that platform.

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Before you schedule the job.

Answers about PostgreSQL setup, available source data, schedules, table updates, and SQL use cases.

Does my PostgreSQL database need to exist before I connect it?

Yes. Connect an existing PostgreSQL database first. The Catchr job creates and populates the destination table you configure inside that database.

Can I load several marketing sources into the same Postgres database?

Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.

Still have a question ? 

Our teams is always here to responds to any question you could have about our data connector. 

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